Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
6th Edition
ISBN: 9781337115186
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 16.1, Problem 1E

Consider the following data for two variables, x and y.

Chapter 16.1, Problem 1E, Consider the following data for two variables, x and y.

Develop an estimated regression equation

  1. a. Develop an estimated regression equation for the data of the form y ^ = b 0 + b 1 x .
  2. b. Using the results from part (a), test for a significant relationship between x and y; use α = .05.
  3. c. Develop a scatter diagram for the data. Does the scatter diagram suggest an estimated regression equation of the form y ^ = b 0 + b 1 x + b 2 x 2 ? Explain.
  4. d. Develop an estimated regression equation for the data of the form y ^ = b 0 + b 1 x + b 2 x 2 .
  5. e. Refer to part (d). Is the relationship between x, x2, and y significant? Use α = .05.
  6. f. Predict the value of y when x = 25.
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create graph of the two-variable data with a regression line, r, r2, and separate residual plot
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.01 level of significance.   Average Temperatures and Snow Accumulations Average Temperature (℉℉) 45 34 24 45 39 20 31 19 35 44 Snow Accumulation (in.in.) 9 16 24 9 15 28 25 18 16 5 1. Regression equation: y=__________ 2. Is the equation appropriate? yes or no
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.010.01 level of significance.   Average Temperatures and Snow Accumulations Average Temperature (℉℉) 38 30 17 39 45 22 34 24 29 38 Snow Accumulation (in.in.) 6 19 27 5 13 26 26 14 13 5 Copy Data

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Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)

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